Articles | Volume 19, issue 16
https://doi.org/10.5194/acp-19-11031-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-11031-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Fine particulate matter (PM2.5) trends in China, 2013–2018: separating contributions from anthropogenic emissions and meteorology
Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological
Administration, Collaborative Innovation Center on Forecast and Evaluation
of Meteorological Disasters, School of Atmospheric Physics, Nanjing
University of Information Science and Technology, Nanjing 210044, China
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, Massachusetts 02138, USA
Daniel J. Jacob
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, Massachusetts 02138, USA
Xuan Wang
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, Massachusetts 02138, USA
Lu Shen
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, Massachusetts 02138, USA
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, Massachusetts 02138, USA
Yuzhong Zhang
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, Massachusetts 02138, USA
Key Laboratory for Atmospheric Chemistry, Chinese Academy of
Meteorological Sciences, CMA, Beijing 100081, China
Tianliang Zhao
Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological
Administration, Collaborative Innovation Center on Forecast and Evaluation
of Meteorological Disasters, School of Atmospheric Physics, Nanjing
University of Information Science and Technology, Nanjing 210044, China
Hong Liao
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, School of Environmental Science and
Engineering, Nanjing University of Information Science and Technology,
Nanjing 210044, China
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Latest update: 24 Dec 2024
Short summary
Observed annual mean PM2.5 decreased by 30–50 % in China from 2013–2018. However, meteorologically PM2.5 variability complicates trend attribution. We used a stepwise multiple linear regression model to quantitatively separate contributions from anthropogenic emissions and meteorology. Results show that 88 % of the PM2.5 decrease across China is attributable to anthropogenic emission changes, and 12 % is attributable to meteorology.
Observed annual mean PM2.5 decreased by 30–50 % in China from 2013–2018. However,...
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